Abstract
When delivering a transport service, scheduled driver workplans have to be aligned with world wide complex hours of service (HoS) regulations which constraint the amount of working and driving time without resting. The activities of such workplans are recorded by onboard sensors in large temporal event logs. Transport companies are interested on recognizing what a driver is doing, based on the temporal observations from event logs, considering the terms defined by HoS regulations. This work presents an application of temporal HTN planning to plan and goal recognition that, starting from a real event log extracted from a tachograph, identifies different sub-sequences of a driver's daily and weekly driving activity and labels them according to the terms defined by HoS regulation.
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